Towards in silico prediction of immunogenic epitopes

Trends Immunol. 2003 Dec;24(12):667-74. doi: 10.1016/j.it.2003.10.006.

Abstract

As torrents of new data now emerge from microbial genomics, bioinformatic prediction of immunogenic epitopes remains challenging but vital. In silico methods often produce paradoxically inconsistent results: good prediction rates on certain test sets but not others. The inherent complexity of immune presentation and recognition processes complicates epitope prediction. Two encouraging developments - data driven artificial intelligence sequence-based methods for epitope prediction and molecular modeling methods based on three-dimensional protein structures - offer hope for the future.

Publication types

  • Review

MeSH terms

  • Animals
  • Antigen Presentation / immunology
  • Epitopes, T-Lymphocyte / chemistry
  • Epitopes, T-Lymphocyte / immunology*
  • Humans
  • Models, Immunological*
  • Models, Molecular
  • Protein Binding / immunology

Substances

  • Epitopes, T-Lymphocyte